Stochastic Modelling For Risk Assessment

He, Yaping; Horasan, Mahmut; Taylor, Patricia; Ramsay, G. Caird

doi:10.3801/iafss.fss.7-333

Cited by 17 publications

(12 citation statements)

References 12 publications

(14 reference statements)

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“…It has long been recognized that design parameters are associated with uncertainties due to the complex nature of reality. As a consequence, these parameters become random variables [5,[9][10][11][12]. To deal with such uncertainties, engineering design analyses can be carried out on three levels, as suggested by Frantzich et al [13].…”

Section: Introductionmentioning

confidence: 99%

Linking Safety Factor and Failure Probability for Fire Safety Engineering

2010

Journal of Fire Protection Engineering

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In response to the call for the development of risk informed, performance-based building fire regulations, a literature review was conducted to link the traditional safety factor approach in fire safety engineering to failure probability. It can be demonstrated that a safety factor alone is an insufficient measure, or is only a first-order measure of risk or failure probability. To achieve a higher order estimate of failure probability, an-percentile method is proposed. As part of this methodology, it is also proposed that the fire engineering briefing process involve nominations of percentile values for design fire scenarios as well as other parameters that define the scenarios.

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Section: Introductionmentioning

confidence: 99%

Linking Safety Factor and Failure Probability for Fire Safety Engineering

2010

Journal of Fire Protection Engineering

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“…Moreover, many fire risk assessment methods have made considerable progress under the effort of fire scientists and engineers. He et al (4) presented a fire risk assessment method by incorporating stochastic modeling techniques for calculating the expected number of deaths. Risk profile and average risk to occupants were employed to express risk severity based on event tree analysis.…”

Section: Introductionmentioning

confidence: 99%

Quantitative Assessment of Building Fire Risk to Life Safety

Chu

Sun

2008

Risk Analysis

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This article presents a quantitative risk assessment framework for evaluating fire risk to life safety. Fire risk is divided into two parts: probability and corresponding consequence of every fire scenario. The time-dependent event tree technique is used to analyze probable fire scenarios based on the effect of fire protection systems on fire spread and smoke movement. To obtain the variation of occurrence probability with time, Markov chain is combined with a time-dependent event tree for stochastic analysis on the occurrence probability of fire scenarios. To obtain consequences of every fire scenario, some uncertainties are considered in the risk analysis process. When calculating the onset time to untenable conditions, a range of fires are designed based on different fire growth rates, after which uncertainty of onset time to untenable conditions can be characterized by probability distribution. When calculating occupant evacuation time, occupant premovement time is considered as a probability distribution. Consequences of a fire scenario can be evaluated according to probability distribution of evacuation time and onset time of untenable conditions. Then, fire risk to life safety can be evaluated based on occurrence probability and consequences of every fire scenario. To express the risk assessment method in detail, a commercial building is presented as a case study. A discussion compares the assessment result of the case study with fire statistics.

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“…A stochastic approach was proposed by He et al [9], in which the building evacuation process is treated as a counting process that follows the Poisson distribution. The determination of the sole parameter of the Poisson distribution, namely, the population flow rate, was based on the conventional deterministic approach and therefore, has limited scope.…”

Section: Introductionmentioning

confidence: 99%

A Stochastic Approach To Occupant Pre-movement In Fires

Vistnes¹,

Grubits²,

He³

2005

Fire Safety Science - Proceedings of the Eigth International Sy

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A stochastic model has been developed to estimate the pre-movement time of occupants in a fire situation. The model quantifies the response and delay periods using probability distribution functions and Monte Carlo simulation techniques. The model takes into account both the occupants and building characteristics. The times spent on various delay actions by the occupant are treated as random variables with prescribed distribution functions. When a delay action is related to a quantifiable occupant or building characteristic, the associated parameter is also assumed to be a random parameter and the appropriate governing distribution is assigned. The model produces, for a given building design and occupant group, the probability distribution of pre-movement time and the related parameters. The results of simulation runs are presented in this paper. The results correlate reasonably well with the data obtained from the literature. Sensitivity studies are also carried out and the regression and correlation are analysed.

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Stochastic Modelling For Risk Assessment

Cited by 17 publications

References 12 publications

Linking Safety Factor and Failure Probability for Fire Safety Engineering

Linking Safety Factor and Failure Probability for Fire Safety Engineering

Quantitative Assessment of Building Fire Risk to Life Safety

A Stochastic Approach To Occupant Pre-movement In Fires

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